`airflow.providers.google.cloud.sensors.dataproc`¶

This module contains a Dataproc Job sensor.

Module Contents¶

Classes¶

`DataprocJobSensor`	Check for the state of a previously submitted Dataproc job.
`DataprocBatchSensor`	Check for the state of batch.

class airflow.providers.google.cloud.sensors.dataproc.DataprocJobSensor(*, dataproc_job_id, region, project_id=None, gcp_conn_id='google_cloud_default', wait_timeout=None, **kwargs)[source]¶

Bases: airflow.sensors.base.BaseSensorOperator

Check for the state of a previously submitted Dataproc job.

Parameters

dataproc_job_id (str) – The Dataproc job ID to poll. (templated)
region (str) – Required. The Cloud Dataproc region in which to handle the request. (templated)
project_id (str | None) – The ID of the google cloud project in which to create the cluster. (templated)
gcp_conn_id (str) – The connection ID to use connecting to Google Cloud Platform.
wait_timeout (int | None) – How many seconds wait for job to be ready.

template_fields: Sequence[str] = ('project_id', 'region', 'dataproc_job_id')[source]¶

ui_color = '#f0eee4'[source]¶

execute(context)[source]¶

This is the main method to derive when creating an operator. Context is the same dictionary used as when rendering jinja templates.

Refer to get_template_context for more context.

poke(context)[source]¶

Function defined by the sensors while deriving this class should override.

class airflow.providers.google.cloud.sensors.dataproc.DataprocBatchSensor(*, batch_id, region, project_id=None, gcp_conn_id='google_cloud_default', wait_timeout=None, **kwargs)[source]¶